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Biomedical subjects

R J Douglas

Publications and source records attributed to R J Douglas.

At least 19 recordsLinked to original sources
PubMed2000

Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit.

Digital circuits such as the flip-flop use feedback to achieve multistability and nonlinearity to restore signals to logical levels, for example 0 and 1. Analogue feedback circuits are generally designed to operate linearly, so that signals are over a range, and the response is unique. By contrast, the response of cortical circuits to sensory stimulation can be both multistable and graded. We propose that the neocortex combines digital selection of an active set of neurons with analogue response by dynamically varying the positive feedback inherent in its recurrent connections. Strong positive feedback causes differential instabilities that drive the selection of a set of active neurons under the constraints embedded in the synaptic weights. Once selected, the active neurons generate weaker, stable feedback that provides analogue amplification of the input. Here we present our model of cortical processing as an electronic circuit that emulates this hybrid operation, and so is able to perform computations that are similar to stimulus selection, gain modulation and spatiotemporal pattern generation in the neocortex.

Electrophysiology↗
PubMed1999

Feedback interactions between neuronal pointers and maps for attentional processing.

Neural networks combining local excitatory feedback with recurrent inhibition are valuable models of neocortical processing. However, incorporating the attentional modulation observed in cortical neurons is problematic. We propose a simple architecture for attentional processing. Our network consists of two reciprocally connected populations of excitatory neurons; a large population (the map) processes a feedforward sensory input, and a small population (the pointer) modulates location and intensity of this processing in an attentional manner dependent on a control input to the pointer. This pointer-map network has rich dynamics despite its simple architecture and explains general computational features related to attention/intention observed in neocortex, making it interesting both theoretically and experimentally.

Attention↗
PubMed1999

Integrating neuromorphic action-oriented perceptual inputs to generate a navigation behaviour for a robot.

We use neural networks with pointer map architectures to provide simple attentional processing in a robotic task. A pointer map comprises a map of neurons that encode a stimulus. Besides global feedback inhibition, the map receives feedback excitation via a small group of pointer neurons that encode the location of a salient stimulus on the map as a vectorial representation. The pointer neurons are able to apply selective processing to a particular region of the network. The robot uses these properties to manoeuver in relation to an attended object. We implemented a controller composed of two pointer maps, and a motor map. The first pointer map reports the direction of a salient obstacle in a one-dimensional map of distance derived from infrared sensors. The second pointer map reports the direction to potential obstacles in a two-dimensional edge-enhanced image derived from a forward looking CCD-camera. These outputs are applied to a motor map, where they bias the motor control signals issued to the robots wheels, according to navigational intentions.

Avoidance Learning↗
PubMed1997

An intracellular study of the contrast-dependence of neuronal activity in cat visual cortex.

Extracellular recordings indicate that mechanisms that control contrast gain of neuronal discharge are found in the retina, thalamus and cortex. In addition, the cortex is able to adapt its contrast response function to match the average local contrast. Here we examine the neuronal mechanism of contrast adaptation by direct intracellular recordings in vivo. Both simple (n = 3) and complex cells (n = 4) show contrast adaptation during intracellular recording. For simple cells, that the amplitude of fluctuations in membrane potential induced by a drifting grating stimulus follows a contrast response relation similar to lateral geniculate relay cells, and does not reflect the high gain and adaptive properties seen in the action potential discharge of the neurons. We found no evidence of significant shunting inhibition that could explain these results. In complex cells there was no change in the mean membrane potential for different contrast stimuli or different states of adaptation, despite marked changes in discharge rate. We use a simplified electronic model to discuss the central features of our results and to explain the disparity between the contrast response functions of the membrane potential and action potential discharge in simple cells.

Action Potentials↗
PubMed1996

The role of synapses in cortical computation.

The synapse, first introduced as physiological hypothesis by C.S. Sherrington at the close of the nineteenth century, has, 100 years on, become the nexus for anatomical and functional investigations of interneuronal communication. A number of hypotheses have been proposed that give local synaptic interactions specific roles in generating an algebra or logic for computations in the neocortex. Experimental work, however, has provided little support for such schemes. Instead, both structural and functional studies indicate that characteristically cortical functions, e.g., the identification of the motion or orientation of objects, involve computations that must be achieved with high accuracy through the collective action of hundreds or thousands of neurons connected in recurrent microcircuits. Some important principles that emerge from this collective action can effectively be captured by simple electronic models. More detailed models explain the nature of the complex computations performed by the cortical circuits and how the computations remain so remarkably robust in the face of a number of sources of noise, including variability in the anatomical connections, large variance in the synaptic responses and in the trial-to-trial output of single neurons, and weak or degraded input signals.

Animals↗
PubMed1996

Comparison of discharge variability in vitro and in vivo in cat visual cortex neurons.

1. In neocortical slices, the majority of neurons fire quite regularly in response to constant current injections. But neurons in the intact animal fire irregularly in response to constant current injection as well as to visual stimuli. 2. To quantify this observation, we developed a new measure of variability, which compares only adjacent interspike intervals and is therefore less sensitive to rate variations than existing measures such as the coefficient of variation of interspike intervals. 3. We find that the variability of firing is much higher in cells of primary visual cortex in the anesthetized cat than in slice. The response to current injected from an intracellular electrode in vivo is also variable, but slightly more regular and less bursty than in response to visual stimuli. 4. Using a new technique for analyzing the variability of integrate-and-fire neurons, we prove that this behavior is consistent with a simple integrate-and-fire model receiving a large amount of synaptic background activity, but not with a noisy spiking mechanism.

Animals↗
PubMed1995

Recurrent excitation in neocortical circuits.

The majority of synapses in the mammalian cortex originate from cortical neurons. Indeed, the largest input to cortical cells comes from neighboring excitatory cells. However, most models of cortical development and processing do not reflect the anatomy and physiology of feedback excitation and are restricted to serial feedforward excitation. This report describes how populations of neurons in cat visual cortex can use excitatory feedback, characterized as an effective "network conductance", to amplify their feedforward input signals and demonstrates how neuronal discharge can be kept proportional to stimulus strength despite strong, recurrent connections that threaten to cause runaway excitation. These principles are incorporated into models of cortical direction and orientation selectivity that emphasize the basic design principles of cortical architectures.

Animals↗
PubMed1995

Do neurons have a voltage or a current threshold for action potential initiation?

The majority of neural network models consider the output of single neurons to be a continuous, positive, and saturating firing rate f (t), while a minority treat neuronal output as a series of delta pulses sigma delta (t-ti). We here argue that the issue of the proper output representation relates to the biophysics of the cells in question and, in particular, to whether initiation of somatic action potentials occurs when a certain threshold voltage or a threshold current is exceeded. We approach this issue using numerical simulations of the electrical behavior of a layer 5 pyramidal cell from cat visual cortex. The dendritic tree is passive while the cell body includes eight voltage- and calcium-dependent membrane conductances. We compute both the steady-state (Istatic(infinity)(Vm)) and the instantaneous (I0(Vm)) I-V relationships and argue that the amplitude of the local maximum in Istatic(infinity)(Vm) corresponds to the current threshold Ith for sustained inputs, while the location of the middle zero-crossing of I0 corresponds to a fixed voltage threshold Vth for rapid inputs. We confirm this using numerical simulations: for "rapid" synaptic inputs, spikes are initiated if the somatic potential exceeds Vth, while for slowly varying input Ith must be exceeded. Due to the presence of the large dendritic tree, no charge threshold Qth exists for physiological input. Introducing the temporal average of the somatic membrane potential while the cell is spiking repetitively, allows us to define a dynamic I-V relationship Idynamic(infinity)( ). We find an exponential relationship between and the net current sunk by the somatic membrane during spiking (diode-like behavior). The slope of Idynamic(infinity)( ) allows us to define a dynamic input conductance and a time constant that characterizes how rapidly the cell changes its output firing frequency in response to a change in its input.

Action Potentials↗
PubMed1994

Synaptic output of physiologically identified spiny stellate neurons in cat visual cortex.

Spiny stellate neurons of area 17 of the cat's visual cortex were physiologically characterised and injected intracellularly with horseradish peroxidase. Six neurons from sublamina 4A were selected. Five had the S-type of simple receptive fields; one had a complex receptive field. Their axons formed boutons mainly in layers 3 and 4. An electron microscopic examination of 45 boutons showed that each bouton formed one asymmetric synapse on average. Spines were the most frequent synaptic target (74%); dendritic shafts formed the remainder (26%). On the basis of ultrastructural characteristics, 8% of the target dendrites were characterised as originating from smooth gamma-aminobutyrate-ergic (GABAergic) neurons. Thus the major output of spiny stellate neurons is to other spiny neurons, probably pyramidal neurons in layer 3 and spiny stellates in layer 4.

Animals↗
PubMed1994

Map of the synapses formed with the dendrites of spiny stellate neurons of cat visual cortex.

The synaptic input of six spiny stellate neurons in sublamina 4A of cat area 17 was assessed by electron microscopy. The neurons were physiologically characterized and filled with horseradish peroxidase in vivo. After processing the neurons were reconstructed at the light microscopic level using computer-assisted methods and analyzed quantitatively. The extensive branching of the dendritic tree about 50 microns from the soma meant that the distal branches constituted five times the length of proximal dendrite. Proximal and distal portions of a single dendrite from each neuron were examined in series of ultrathin sections (1,456 sections) in the electron microscope. The majority (79%) of the 263 synapses examined were asymmetric; the remainder (21%) were symmetric. Symmetric synapses formed 35% of synapses sampled on proximal dendrites and were usually located on the shaft. They formed only 4% of synapses sampled on distal dendrites. Spines accounted for less than half of the total asymmetric synapses (45%); the remainder were on shafts. Symmetric synapses formed with four of 92 spines. Nine spines formed no synapses. Spiny stellate neurons in cat visual cortex appear to differ considerably from pyramidal neurons in having a significant asymmetric (excitatory) synaptic input to the dendritic shaft.

Animals↗
PubMed1994

Polyneuronal innervation of spiny stellate neurons in cat visual cortex.

Our hypothesis was that spiny stellate neurons in layer 4 of cat visual cortex receive polyneuronal innervation. We characterised the synapses of four likely sources of innervation by three simple criteria: the type of synapse, the target (spine, dendritic shaft), and the area of the presynaptic bouton. The layer 6 pyramids had the smallest boutons and formed asymmetric synapses mainly with the dendritic shaft. The thalamic afferents had the largest boutons and formed asymmetric synapses mainly with spines. The spiny stellates had medium-sized boutons and formed asymmetric synapses mainly with spines. We used these to make a "template" to match against the boutons forming synapses with the spiny stellate dendrite. Of the asymmetric synapses, 45% could have come from layer 6 pyramidal neurons, 28% from spiny stellate neurons, and 6% from thalamic afferents. The remaining 21% of asymmetric synapses could not be accounted for without assuming some additional selectivity of the presynaptic axons. Additional asymmetric synapses may come from a variety of sources, including other cortical neurons and subcortical nuclei such as the claustrum. Of the symmetric synapses, 84% could have been provided by clutch cells, which form large boutons. The remainder, formed by small boutons, probably come from other smooth neurons in layer 4, e.g., neurogliaform and bitufted neurons. Our analysis supports the hypothesis that the spiny stellate receives polyneuronal innervation, perhaps from all the sources of boutons in layer 4. Although layer 4 is the major recipient of thalamic afferents, our results show that they form only a few percent of the synapses of layer 4 spiny stellate neurons.

Animals↗
PubMed1994

Amplification and linearization of distal synaptic input to cortical pyramidal cells.

1. Computer simulations were used to study the effect of voltage-dependent calcium and potassium conductances in the apical dendritic tree of a pyramidal cell on the synaptic efficacy of apical synaptic input. The apical tuft in layers 1 and 2 is the target of feedback projections from other cortical areas. 2. The current, Isoma, flowing into the soma in response to synaptic input was used to assess synaptic efficacy. This measure takes full account of all the relevant nonlinearities in the dendrities and can be used during spiking activity. Isoma emphasizes current flowing in response to synaptic input rather than synaptically induced voltage change. This measure also permits explicit characterization of the input-output relationship of the entire neuron by computing the relationship between presynaptic input and postsynaptic output frequency. 3. Simulations were based on two models. The first was a biophysically detailed 400-compartment model of a morphologically characterized layer 5 pyramidal cell from striate cortex of an adult cat. In this model eight voltage-dependent conductances were incorporated into the somatic membrane to provide the observed firing behavior of a regular spiking cell. The second model was a highly simplified three-compartment equivalent electrical circuit. 4. If the dendritic tree is entirely passive, excitatory synaptic input of the non-N-methyl-D-aspartate (non-NMDA) type to layers 1, 2, and 3 saturate at very moderate input rates, because of the high input impedance of the apical tuft. Layers 1 and 2 together can deliver only 0.25 nA current to the soma. This modest effect is surprising in view of the important afferents that synapse on the apical tuft and is inconsistent with experimental data indicating a more powerful effect. 5. We introduced in a controlled manner a voltage-dependent potassium conductance in the apical tuft, gK, to prevent saturation of the synaptic response. This conductance was designed to linearize the relationship between presynaptic input frequency and the somatic current. We also introduced a voltage-dependent calcium conductance along the apical trunk, gCa, to amplify the apical signal, i.e., the synaptic current reaching the soma. 6. To arrive at a specific relationship between the presynaptic input rate and the somatic current delivered by the synaptic input, we derived the activation curves of gK and gCa either analytically or numerically. The resultant voltage-dependent behavior of both conductances was similar to experimentally measured activation curves.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗
PubMed1993

Experimental modes of Caryospora bigenetica (Apicomplexa: Eimeriidae) infection in swine and the effects of temperature and salinity on parasite infectivity in porcine tissue.

Four crossbred pigs (Sus scrofa) were inoculated orally with Caryospora bigenetica oocysts derived from snake and mouse feces, and with C. bigenetica infected mouse tissue. One pig also was given i.m. injections of methylprednisolone acetate. All four pigs displayed clinical signs including erythema, edema, and lethargy. Caryocysts were observed histologically in numerous tissues including ear, tongue, jowl, shoulder, loin, intercostal, ham, hock, and feet. The four pigs each were butchered into six commercial cuts: shoulder, loin, side, ham, hock, and feet. Raw 10 g samples from each cut were bioassayed by pepsin digestion and s.c. inoculation into 12 Swiss-Webster mice (Mus musculus) and 12 cotton rats (Sigmodon hispidus). Seventeen of 24 mice and cotton rats exhibited clinical signs and C. bigenetica tissue infections. Remaining portions of the six commercial cuts were temperature or saline treated, and 10 g samples were bioassayed in 16 mice and 12 cotton rats. No clinical sign or tissue infection was observed in these animals. Our study presents evidence that swine can be infected with C. bigenetica by ingesting oocysts present in snake feces or mouse feces (following inoculation of mice with snake-derived oocysts) or by ingesting C. bigenetica infected rodent tissue, that endogenously produced C. bigenetica oocysts are not excreted in the feces of swine, and that C. bigenetica in pork can be rendered noninfective by freezing at -20 degrees C (-4 degrees F) for 21 days, frying at 84 degrees C (183 degrees F) for 17 min, microwaving at 88 degrees C (190 degrees F) for 17 min, grilling at 82 degrees C (180 degrees F) for 48 min, baking at 95 degrees C (203 degrees F) for 230 min, boiling at 100 degrees C (212 degrees F) for 60 min, or by curing at 4 degrees C (39 degrees F) for 20 days.

Animals↗
PubMed1993

The neurobiology of primate vision.

Studies of the visual system of the primate have taken two directions. One group of neurobiologists have studied the oculomotor system, while an entirely separate group have analysed sensory processing in the retinogeniculo-cortical circuits. However, the versatility and adaptability of the primate visual system is only possible because sensory and oculomotor processing are highly integrated. More than any other species, primates have exploited the advantages of extensive and coordinated binocular eye movements to improve their visuomotor performance. This chapter describes the basic apparatus of primate vision. The integrated nature of visuomotor function is illustrated by two examples: smooth pursuit eye movements and stereovision. Both of these tasks require huge amounts of sensory processing in many different visual centres and, simultaneously, very precise control of binocular eye position. These examples illustrate the difficulty and artificiality of assigning unique functions to any component part of the system. Each part of the visual system, from the retina through the brain to the oculomotoneurones that drive the eye muscles, is involved in many different functions. This integration within the system raises the problem of how we represent and recognize our visual world in the brain. The traditional view from sensory psychology is that single nerve cells in the visual cortex signal significant percepts. As this chapter shows, the activity of single cortical neurones is influenced by multiple factors, including the qualities of the visual stimulus, the position of the eyes, and the attention being paid to the stimulus. Thus, the activity of single neurones is an ambiguous indicator of both perceptual and motor events. Only the collective action of many nerve cells, it seems, represents unique percepts and actions. Given this indivisibility of function, patients with localized brain lesions will invariably present with multiple visuomotor deficits.

Animals↗